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方法族Process / pipelineProcess / pipeline
起源年份1950s (Berelson 1952; Krippendorff 1980/2004)1950s onward; longitudinal application widely adopted in media research by the 1970s–1980s
提出者Bernard Berelson; later systematised by Klaus KrippendorffDeveloped within communication and media studies; codified by Berelson (1952) and extended by Riffe, Lacy, Fico
类型Quantitative observational research methodQuantitative observational research design
开创性文献Krippendorff, K. (2004). Content Analysis: An Introduction to Its Methodology (2nd ed.). Sage. ISBN: 978-0761915454Riffe, D., Lacy, S., Watson, B., & Fico, F. (2019). Analyzing Media Messages: Using Quantitative Content Analysis in Research (4th ed.). Routledge. ISBN: 9781138490536
别名QCA, manifest content analysis, systematic content analysis, frequency-based content analysislongitudinal content analysis, repeated-measure content analysis, time-series content analysis, longitudinal QCA
相关45
摘要Quantitative content analysis is a systematic, replicable method for converting the manifest content of text, images, or other recorded communication into numerical data. By applying a pre-specified codebook to a defined corpus and counting or scaling the resulting categories, researchers obtain frequency distributions, proportions, and relationships that can be subjected to standard statistical tests. It is the dominant method for large-scale, objective analysis of media, documents, social media posts, policy texts, and similar materials.Longitudinal quantitative content analysis systematically codes and counts features of texts, images, or media messages gathered at two or more points in time, enabling researchers to track how content changes, how themes rise or fall in prevalence, and how media or institutional messaging responds to external events. The design merges the structured measurement logic of quantitative content analysis with the temporal tracking power of longitudinal observation.
ScholarGate数据集
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ScholarGate方法对比: Quantitative Content Analysis · Longitudinal Quantitative Content Analysis. 于 2026-06-17 检索自 https://scholargate.app/zh/compare